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Artificial intelligence techniques in IC chip marking

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Main Authors: Muthukaruppan, Kartigayan, Nagarajan, R., Sazali, Yaacob, Pandian, Paulraj, Mohamed Rizon, Mohamed Juhari
Format: Article
Language:English
Published: Kolej Universiti Kejuruteraan Utara Malaysia 2008
Subjects:
Integrated circuits
Artificial intelligence
Optical Character Recognition (OCR)
Optical character recognition devices
Integrated circuits > Inspection
Integrated circuits > Design and construction
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/2288
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spelling my.unimap-22882009-09-04T03:06:26Z Artificial intelligence techniques in IC chip marking Muthukaruppan, Kartigayan Nagarajan, R. Sazali, Yaacob Pandian, Paulraj Mohamed Rizon, Mohamed Juhari Integrated circuits Artificial intelligence Optical Character Recognition (OCR) Optical character recognition devices Integrated circuits -- Inspection Integrated circuits -- Design and construction Link to publisher's homepage at http://www.unimap.edu.my/ In this paper, an industrial machine vision system incorporating Optical Character Recognition (OCR) is employed to inspect the marking on the Integrated Circuit (IC) Chips. This inspection is carried out while the ICs are coming out from the manufacturing line. A TSSOP-DGG type of IC package from Texas Instrument is used in this investigation. The IC chips markings are laser printed. This inspection system tests are laser printed marking on IC chips and are according to the specifications. Artificial intelligence (AI) techniques are used in this inspection. AI techniques utilized are neural network and fuzzy logic. The inspection is earned out to find the print errors; such as illegible character, upside down print and missing characters. The vision inspection of the printed markings on the IC chip is carried out in three phases, namely, image preprocessing, feature extraction and classification. MATLAB platform and its toolboxes are used for designing the inspection processing technique. The percentage of accuracy of the classification is found to be between 97% -100%. 2008-09-16T06:46:19Z 2008-09-16T06:46:19Z 2005 Article Journal of Engineering Research and Education, vol. 2, 2005, pages 17-29. 1823-2981 http://hdl.handle.net/123456789/2288 http://www.unimap.edu.my/ en Kolej Universiti Kejuruteraan Utara Malaysia
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Integrated circuits
Artificial intelligence
Optical Character Recognition (OCR)
Optical character recognition devices
Integrated circuits -- Inspection
Integrated circuits -- Design and construction
spellingShingle Integrated circuits
Artificial intelligence
Optical Character Recognition (OCR)
Optical character recognition devices
Integrated circuits -- Inspection
Integrated circuits -- Design and construction
Muthukaruppan, Kartigayan
Nagarajan, R.
Sazali, Yaacob
Pandian, Paulraj
Mohamed Rizon, Mohamed Juhari
Artificial intelligence techniques in IC chip marking
description Link to publisher's homepage at http://www.unimap.edu.my/
format Article
author Muthukaruppan, Kartigayan
Nagarajan, R.
Sazali, Yaacob
Pandian, Paulraj
Mohamed Rizon, Mohamed Juhari
author_facet Muthukaruppan, Kartigayan
Nagarajan, R.
Sazali, Yaacob
Pandian, Paulraj
Mohamed Rizon, Mohamed Juhari
author_sort Muthukaruppan, Kartigayan
title Artificial intelligence techniques in IC chip marking
title_short Artificial intelligence techniques in IC chip marking
title_full Artificial intelligence techniques in IC chip marking
title_fullStr Artificial intelligence techniques in IC chip marking
title_full_unstemmed Artificial intelligence techniques in IC chip marking
title_sort artificial intelligence techniques in ic chip marking
publisher Kolej Universiti Kejuruteraan Utara Malaysia
publishDate 2008
url http://dspace.unimap.edu.my/xmlui/handle/123456789/2288
_version_ 1643787577871826944
score 13.214268

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